{"id":"https://openalex.org/W4402474809","doi":"https://doi.org/10.1109/ccece59415.2024.10667211","title":"Sample-Efficient Meta-RL for Traffic Signal Control","display_name":"Sample-Efficient Meta-RL for Traffic Signal Control","publication_year":2024,"publication_date":"2024-08-06","ids":{"openalex":"https://openalex.org/W4402474809","doi":"https://doi.org/10.1109/ccece59415.2024.10667211"},"language":"en","primary_location":{"id":"doi:10.1109/ccece59415.2024.10667211","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ccece59415.2024.10667211","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060683531","display_name":"Xingshuai Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Xingshuai Huang","raw_affiliation_strings":["McGill University,Canada"],"affiliations":[{"raw_affiliation_string":"McGill University,Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022267948","display_name":"Di Wu","orcid":"https://orcid.org/0000-0001-7419-9903"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Di Wu","raw_affiliation_strings":["McGill University,Canada"],"affiliations":[{"raw_affiliation_string":"McGill University,Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058737924","display_name":"Michael Jenkin","orcid":"https://orcid.org/0000-0002-2969-0012"},"institutions":[{"id":"https://openalex.org/I192455969","display_name":"York University","ror":"https://ror.org/05fq50484","country_code":"CA","type":"education","lineage":["https://openalex.org/I192455969"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Michael Jenkin","raw_affiliation_strings":["York University,Canada"],"affiliations":[{"raw_affiliation_string":"York University,Canada","institution_ids":["https://openalex.org/I192455969"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081097070","display_name":"Beno\u00eet Boulet","orcid":"https://orcid.org/0000-0002-3191-3967"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Benoit Boulet","raw_affiliation_strings":["McGill University,Canada"],"affiliations":[{"raw_affiliation_string":"McGill University,Canada","institution_ids":["https://openalex.org/I5023651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5060683531"],"corresponding_institution_ids":["https://openalex.org/I5023651"],"apc_list":null,"apc_paid":null,"fwci":0.3297,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57786333,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"312","last_page":"318"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10791","display_name":"Advanced Control Systems Optimization","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10142","display_name":"Formal Methods in Verification","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.6432977914810181},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6036108136177063},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5102355480194092},{"id":"https://openalex.org/keywords/traffic-signal","display_name":"Traffic signal","score":0.41507017612457275},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.23056548833847046}],"concepts":[{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.6432977914810181},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6036108136177063},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5102355480194092},{"id":"https://openalex.org/C2987419075","wikidata":"https://www.wikidata.org/wiki/Q8004","display_name":"Traffic signal","level":2,"score":0.41507017612457275},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.23056548833847046},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccece59415.2024.10667211","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ccece59415.2024.10667211","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1491843047","https://openalex.org/W2064675550","https://openalex.org/W2145339207","https://openalex.org/W2809148419","https://openalex.org/W2998332605","https://openalex.org/W3037546475","https://openalex.org/W3038822267","https://openalex.org/W4226017951","https://openalex.org/W4288319859","https://openalex.org/W4288357413","https://openalex.org/W4311405210","https://openalex.org/W4313547795","https://openalex.org/W4313555308","https://openalex.org/W4315706776","https://openalex.org/W4324298583","https://openalex.org/W4382318215","https://openalex.org/W4385245566","https://openalex.org/W6736057607","https://openalex.org/W6754471908","https://openalex.org/W6760405395","https://openalex.org/W6764053384","https://openalex.org/W6783988234","https://openalex.org/W6842654171"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2393348402","https://openalex.org/W2242021741","https://openalex.org/W2377015873","https://openalex.org/W2605253768","https://openalex.org/W2392201083"],"abstract_inverted_index":{"Traffic":[0],"congestion":[1],"is":[2,35,71],"a":[3,21,143],"pervasive":[4],"challenge":[5],"in":[6,24,51],"urban":[7],"areas,":[8],"contributing":[9],"significantly":[10],"to":[11,80,112],"greenhouse":[12],"gas":[13],"emissions.":[14],"Efficient":[15],"traffic":[16,42,53,95,136],"signal":[17,54,96,137],"control":[18,138],"stands":[19],"as":[20],"pivotal":[22],"factor":[23],"enhancing":[25,122],"modern":[26],"transportation":[27],"systems.":[28],"The":[29],"complexity":[30],"of":[31,41,67,105,145],"this":[32],"decision-making":[33],"process":[34],"heightened":[36],"by":[37,73],"the":[38,64,103,146,149],"dynamic":[39],"nature":[40],"patterns.":[43],"Reinforcement":[44],"Learning":[45],"(RL)":[46],"approaches":[47],"have":[48],"showcased":[49],"promise":[50],"addressing":[52],"control,":[55],"exhibiting":[56],"notable":[57],"performance":[58],"gains":[59],"over":[60],"traditional":[61],"methods.":[62],"However,":[63],"practical":[65],"utility":[66],"many":[68],"RL-based":[69,135],"solutions":[70],"constrained":[72],"their":[74],"substantial":[75],"data":[76],"requirements,":[77],"limiting":[78],"applicability":[79],"real-world":[81,129],"scenarios.":[82],"This":[83],"paper":[84],"introduces":[85],"an":[86,117],"innovative":[87],"model-based":[88],"meta-reinforcement":[89],"learning":[90],"framework,":[91],"ModelLight,":[92,99],"designed":[93],"for":[94],"control.":[97],"In":[98],"world":[100],"models":[101],"capturing":[102],"dynamics":[104],"signalized":[106],"intersection":[107],"are":[108],"acquired":[109],"and":[110,153],"employed":[111],"generate":[113],"imaginary":[114],"trajectories":[115],"within":[116],"optimization-based":[118],"meta-learning":[119],"approach,":[120],"thereby":[121],"overall":[123],"sample":[124],"efficiency.":[125],"Experimental":[126],"evaluations":[127],"on":[128],"scenarios":[130],"demonstrate":[131],"that":[132],"ModelLight":[133],"surpasses":[134],"baselines":[139],"while":[140],"demanding":[141],"only":[142],"fraction":[144],"interactions":[147],"with":[148],"environment.":[150],"Our":[151],"datasets":[152],"code":[154],"can":[155],"be":[156],"found":[157],"at":[158],"https://github.com/XingshuaiHuang/ModelLight.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}